• Coupled systems mechanics
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• v.10 no.6
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• pp.509-520
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• 2021

Fiber-reinforced concrete (FRC) is a composite material where small fibers made from steel or polypropylene or similar material are embedded into concrete matrix. In a material model each constituent should be adequately described, especially the interface between the matrix and fibers that is determined with the 'bond-slip' law. 'Bond-slip' law describes relation between the force in a fiber and its displacement. Bond-slip relation is usually obtained from tension laboratory experiments where a fiber is pulled out from a matrix (concrete) block. However, theoretically bond-slip relation could be determined from bending experiments since in bending the fibers in FRC get pulled-out from the concrete matrix. We have performed specially designed laboratory experiments of three-point beam bending with an intention of using experimental data for determination of material parameters. In addition, we have formulated simple layered model for description of the behavior of beams in the three-point bending test. It is not possible to use this 'forward' beam model for extraction of material parameters so an inverse model has been devised. This model is a basis for formulation of an inverse model that could be used for parameter extraction from laboratory tests. The key assumption in the developed inverse solution procedure is that some values in the formulation are known and comprised in the experimental data. The procedure includes measured data and its derivative, the formulation is nonlinear and solution is obtained from an iterative procedure. The proposed method is numerically validated in the example at the end of the paper and it is demonstrated that material parameters could be successfully recovered from measured data.

• Industry Promotion Research
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• v.7 no.3
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• pp.17-26
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• 2022

As the well-being mindset to keep our minds and bodies free and healthy more than anything else in the society we live in is spreading, the meaning of health care has become a key part of the 4th industrial revolution such as big data, IoT, AI, and block chain. The advancement of the advanced medical information service industry is being promoted by utilizing convergence technology. In digital healthcare, the development of intelligent information technology such as artificial intelligence, big data, and cloud is being promoted as a digital transformation of the traditional medical and healthcare industry. In addition, due to rapid development in the convergence of science and technology environment, various issues such as health, medical care, welfare, etc., have been gradually expanded due to social change. Therefore, in this study, first, the general meaning and current status of digital health care medical information is examined, and then, developmental tasks to activate digital health care medical information are analyzed and reviewed. The purpose of this article is to improve usability to fully pursue our human freedom.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.1-9
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• 2010

Feistel and SPN are the two main structures in a block cipher. Feistel is a symmetric structure which has the same structure in encryption and decryption, but SPN is not a symmetric structure. In this paper, we propose a SPN which has a symmetric structure in encryption and decryption. The whole operations of proposed algorithm are composed of the even numbers of N rounds where the first half of them, 1 to N/2 round, applies a right function and the last half of them, (N+1)/2 to N round, employs an inverse function. And a symmetry layer is located in between the right function layer and the inverse function layer. In this paper, AES encryption and decryption function are selected for the right function and the inverse function, respectively. The symmetric layer is composed with simple matrix and round key addition. Due to the simplicity of the symmetric SPN structure in hardware implementation, the proposed modified AES is believed to construct a safe and efficient cipher in Smart Card and RFID environments where electronic chips are built in.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.175-182
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• 2023

Differential cryptanalysis is one of the analysis techniques for block ciphers, and uses the property that the output difference with respect to the input difference exists with a high probability. If random data and differential data can be distinguished, data complexity for differential cryptanalysis can be reduced. For this, many studies on deep learning-based neural distinguisher have been conducted. In this paper, a deep learning-based neural distinguisher for PIPO 64/128 is proposed. As a result of experiments with various input differences, the 3-round neural distinguisher for the differential characteristics for 0, 1, 3, and 5-rounds achieved accuracies of 0.71, 0.64, 0.62, and 0.64, respectively. This work allows distinguishing attacks for up to 8 rounds when used with the classical distinguisher. Therefore, scalability was achieved by finding a distinguisher that could handle the differential of each round. To improve performance, we plan to apply various neural network structures to construct an optimal neural network, and implement a neural distinguisher that can use related key differential or process multiple input differences simultaneously.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.296-297
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• 2022

A smart port refers to a port built based on digital technologies such as IoT, big data, AI, and block chain, and refers to a port that minimizes waste of time, space and resources as the only means of survival of the port. Sustainability refers to 'environmental, economic, and social characteristics that enable people to continue to use the environment, ecosystem, or publicly used resources'. It contains the meaning of 'future sustainability' that can be maintained in the future. In the face of the 4th industrial revolution, interest and realization of smart port construction and sustainability are actively progressing around the world. In this study, core indicators of the ESG (Enviornment, Social, Governance) area, which are key elements of sustainable smart ports, were developed,

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.1163-1175
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• 2023

Cholesterol is prone to oxidation, which results in the formation of cholesterol oxidation products (COPs). This occurs because it is a monounsaturated lipid with a double bond on C-5 position. Cholesterol in foods is mostly non-enzymatically oxidized by reactive oxygen species (ROS)-mediated auto-oxidative reaction. The COPs are found in many common foods of animal-origin and are formed during their manufacture process. The formation of COPs is mainly related to the temperature and the heating time the food is processed, storage condition, light exposure and level of activator present such as free radical. The level of COPs in processed foods could reach up to 1-10 % of the total cholesterol depending on the foods. The most predominant COPs in foods including meat, eggs, dairy products as well as other foods of animal origin were 7-ketocholesterol, 7 α-hydroxycholesterol (7α-OH), 7β-hydroxycholesterol (7β-OH), 5,6α-epoxycholesterol (5,6α-EP), 5,6β-epoxycholesterol (5,6β-EP), 25-hydoxycholesterol (25-OH), 20-hydroxycholesterol (20-OH) and cholestanetriol (triol). They are mainly formed non-enzymatically by cholesterol autoxidation. The COPs are known to be potentially more hazardous to human health than pure cholesterol. The procedure to block cholesterol oxidation in foods should be similar to that of lipid oxidation inhibition since both cholesterol and lipid oxidation go through the same free radical mechanism. The formation of COPs in foods can be stopped by decreasing heating time and temperature, controlling storage condition as well as adding antioxidants into food products. This review aims to present, discuss and respond to articles and studies published on the topics of the formation and inhibition of COPs in foods and key factors that might affect cholesterol oxidation. This review may be used as a basic guide to control the formation of COPs in the food industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.6
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• pp.637-652
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• 2015

In the present work, a number of three-dimensional (3D) parametric numerical analyses have been carried out to study the influence of tunnelling on the behaviour of adjacent piles considering the transverse distance of the pile tip from the tunnel. Single piles and $5{\times}5$ piles inside a group with a spacing of 2.5d were considered, where d is the pile diameter. In the numerical modelling, several key issues, such as the tunnelling-induced pile settlements, the interface shear stresses, the relative shear displacements, the axial pile forces, the apparent factors of safety and zone of influence have been rigorously analysed. It has been found that when the piles are inside the influence zone, the pile head settlements are increased up to about 111% compared to those computed from the Greenfield condition. Larger pile settlements and smaller axial pile forces are induced on the piles inside the pile groups than those computed from the single piles since the piles responded as a block with the surrounding ground. Also tensile pile forces are induced associated with the upward resisting skin friction at the upper part of pile and the downward acting skin friction at the lower part of pile. On the contrary, when the piles were outside the influence zone, tunnelling-induced compressive pile forces developed. Based on computed load and displacement relation of the pile, the apparent factor of safety of the piles was reduced up to about 45%. Therefore the serviceability of the piles may be substantially reduced. The pile behaviour, when considering the single piles and the pile groups with regards to the influence zone, has been analysed by considering the key features in great details.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1149-1154
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• 2003

Due to various requirements for the user access control to large databases in the hospitals and the banks, database security has been emphasized. There are many security models for database systems using wide variety of policy-based access control methods. However, they are not functionally enough to meet the requirements for the complicated and various types of access control. In this paper, we propose a database security system that can individually control user access to data groups of various sites and is suitable for the situation where the user's access privilege to arbitrary data is changed frequently. Data group(s) in different sixes d is defined by the table name(s), attribute(s) and/or record key(s), and the access privilege is defined by security levels, roles and polices. The proposed system operates in two phases. The first phase is composed of a modified MAC (Mandatory Access Control) model and RBAC (Role-Based Access Control) model. A user can access any data that has lower or equal security levels, and that is accessible by the roles to which the user is assigned. All types of access mode are controlled in this phase. In the second phase, a modified DAC(Discretionary Access Control) model is applied to re-control the 'read' mode by filtering out the non-accessible data from the result obtained at the first phase. For this purpose, we also defined the user group s that can be characterized by security levels, roles or any partition of users. The policies represented in the form of Block(s, d, r) were also defined and used to control access to any data or data group(s) that is not permitted in 'read ' mode. With this proposed security system, more complicated 'read' access to various data sizes for individual users can be flexibly controlled, while other access mode can be controlled as usual. An implementation example for a database system that manages specimen and clinical information is presented.